Credit Risk Analytics - Team Lead

Summary

The Credit Risk Analytics team lead is responsible for overseeing the development and management of methodologies and analytics for the suite of Wholesale and Counter party credit risk models. The Candidate will manage the Credit Risk Analytics team, a division of the Risk Analytics Team, that partakes in model development over the full life cycle of models from methodology and design to local implementation and validation and, will act as the technical expert setting up the vision and standards for credit risk modeling.

• Manage a team of 5 quantitative developers focused on specialized credit risk analytics supporting credit stress testing, CECL, and rating models.
• Oversee ongoing support and refinement of existing suite of credit models; develop methodology & algorithms for new models and analytics.
• Perform quantitative research to follow current best practice for credit models and conduct analysis of existing model deficiencies and design remediation plans.
• Manage the implementation of model changes, enhancements and remediation plans using advanced statistical tools and techniques.
• Work with stakeholders across business and functional teams including Model Risk Management during model development, validation, and implementation process.
• Define standards and work with IT business partners on model execution platform development and maintenance of existing code for Credit Risk models.
• Identify and quantify limits of model analytics, and design a strategic plan to better integrate and manage such risks.
• Support discussions with regulators and control functions as a subject matter expert.

• Recognized credit risk model expert with 12-15 years of experience at a large financial institution.
• 3+ years of experience managing a team of credit risk quants.
• Advanced degree in Quantitative Finance, Statistics or related quantitative field.
• Deep knowledge of credit risk modeling for wholesale loans with practical implementation experience.
• Expertise in Model Risk Management frameworks, applicable regulations, and best credit modeling industry practices is essential. DFAST/CCAR submission experience preferred.
• Experience with programming languages (Python, R, SAS, Stata), SQL databases, and data visualization tools (Power
  
  BI, Tableau).
• Subject matter expertise in quantitative models and translating into optimal design application.
• Experience supervising code development/update and integration into an analytical platform.
• Strong knowledge in advanced statistics such as:
• Time series modeling using Kalman Filter state space approach
• MCMC Bayesian tool for regime switching
• Mixed modeling approaches
• Decision tree classification
• Unsupervised clustering
• Non-linear optimization methods
• Deep understanding of the main credit risk stress testing parameters’ modeling (TM/PD, LGD, EAD, EL and Rating), including:
• Generalized Vasicek Single Common Factor approach for TM and PD modeling
• Logit space modeling for TM and PD modeling
• Mixed modeling of the LGD bi-modality
• Vintage/cohort approach for charge-off modeling
• Time series clustering for AUF/EAD modeling
• Experience working with external credit data sources to enhance modeling including industry leaders such as S&P, GCD, and Moody’s Analytics.
• Demonstrable experience in managing audit and regulatory interactions.
• Strong project, management and organizational skills.
• Must have ability to communicate effectively with managers and stakeholders that may not have quantitative backgrounds.

The expected base salary ranges from $225,000 - $250,000. Salary offers are based on a wide range of factors including relevant skills, training, experience, education, and, where applicable, certifications and licenses obtained. Market and organizational factors are also considered. In addition to salary and a generous employee benefits package, successful candidates are also eligible to receive a discretionary bonus.

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Mizuho has in place a hybrid working program, with varying opportunities for remote work depending on the nature of the role, needs of your department, as well as local laws and regulatory obligations. Roles in some of our departments have…